<group>
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J = <a href="%pathto:imop.vl_imsmooth;">VL_IMSMOOTH</a>(I,SIGMA) convolves the image I by an isotropic
Gaussian kernel of standard deviation SIGMA.  I must be an array
of doubles. IF the array is three dimensional, the third dimension
is assumed to span different channels (e.g. R,G,B). In this case,
each channel is convolved independently.
</p><p>
<a href="%pathto:imop.vl_imsmooth;">VL_IMSMOOTH</a>() accepts the following options:
</p><dl><dt>
Kernel
</dt><dd><p>
Selects between GAUSSIAN and TRIANGULAR kernels. The triangular
kernel support has 2*SIGMA-1 sampels. Kernels have unit mass.
</p></dd><dt>
Padding
</dt><dd><p>
Selects between ZERO or CONTINUITY padding method to handle the
image boundaries. ZERO extends the input image with zeroes
around the border, and CONTINUITY extends the image with
constant pixels.
</p></dd><dt>
Step
</dt><dd><p>
Sets the subsampling step. A subsampling step of STEP pixels
causes J(1:STEPS:end, 1:STEPS:end, :) to be computed. This is
useful to downsample the image.
</p></dd></dl><p>
See also: <a href="%pathto:vl_help;">VL_HELP</a>().
</p></div></group>
